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As seen on Kickstarter, artificial intelligence is growing exponentially.
There is no doubt about that.
Self-driving cars are clocking millions of miles, IBM Watson is diagnosing patients better than armies of doctors, and Google Deepmind's AlphaGo beat the world champion at Go, a game where intuition plays a key role.
But the more AI advances, the more complex the problems it needs to solve become.
And only deep learning can solve such complex problems and that is why it is at the heart of artificial intelligence.
- Why DeepLearning AZ? - Here are five reasons why we think Deep Learning AZ is truly different and stands out from the crowd of other training programs: . ROBUST STRUCTURE The first and foremost thing we focus on is giving the course a solid structure.
Deep Learning is very broad and complex and to navigate this labyrinth you need a clear and global vision of it.
That is why we group the tutorials into two volumes, which represent the two main branches of Deep Learning: Supervised Deep Learning and Unsupervised Deep Learning.
With each volume focusing on three different algorithms, we found that this is the best framework for mastering deep learning.
. INTUITION TUTORIALS So many courses and books bombard you with theory, math, and coding.
But they forget to explain perhaps the most important part: why you are doing what you are doing.
And that's how this course is so different.
We focus on developing an intuitive *feel* for the concepts behind Deep Learning algorithms.
With our intuition tutorials you will be sure that you understand all the techniques at an instinctive level.
And once you continue with the hands-on coding exercises, you'll see for yourself how much more meaningful your experience will be.
This is a game changer.
. EXCITING PROJECTS Are you tired of courses based on outdated and overused datasets? Yes? Well, then you're in for a treat.
Within this class, we will work on real-world data sets to solve real-world business problems.
(Definitely not the boring digit or iris classification datasets we see in every course.)
In this course we will solve six real-world challenges: Artificial Neural Networks to solve a customer churn problem Convolutional Neural Networks for image recognition Recursive Neural Networks to predict stock prices Self-organizing maps to investigate fraud Boltzmann Machines to create a Recommender System Stacked Autoencoders * to take on Netflix's $1 Million Prize Challenge * Stacked Autoencoders is a brand new technique in Deep Learning that didn't even exist a couple of years ago.
We have not seen this method explained anywhere else in sufficient depth.
. PRACTICAL CODING InDeep Learning AZ we code together with you.
Every hands-on tutorial starts with a blank page and we write the code from scratch.
This way you can follow and understand exactly how the code is put together and what each line means.
Also, We will structure the code on purpose in such a way that you can download it and apply it in your own projects.
In addition, we explain step by step where and how to modify the code to insert YOUR data set, to adapt the algorithm to your needs, to obtain the result you are looking for.
This is a course that naturally extends into your career.
. SUPPORT DURING THE COURSE Have you ever taken a course or read a book where you have questions but can't reach the author? Well, this course is different.
We are fully committed to making this the most disruptive and powerful Deep Learning course on the planet.
With that comes the responsibility of constantly being there when you need our help.
In fact, since we also physically need to eat and sleep, we have assembled a team of professional data scientists to help us.
Whenever you ask a question, you will receive an answer from us within a maximum period of 48 hours.
No matter how complex your query is, we'll be there.
The bottom line is that we want you to succeed.
-The Tools- Tensorflow and Pytorch are the two most popular open source libraries for Deep Learning.
In this course you will learn both! TensorFlow was developed by Google and is used in its speech recognition system, the new Google Photos product, Gmail, Google Search, and much more.
Companies using Tensorflow include AirBnb, Airbus, Ebay, Intel, Uber, and many more.
PyTorch is just as powerful and is being developed by researchers from Nvidia and leading universities: Stanford, Oxford, ParisTech.
Companies that use PyTorch include Twitter, Saleforce, and Facebook.
So which one is better and for what? Well, in this course you will have the opportunity to work with both and understand when Tensorflow is better and when PyTorch is the way to go.
Throughout the tutorials, we compare the two and give you tips and ideas on which might work better in certain circumstances.
The interesting thing is that both libraries are barely over 1 year old.
That's what we mean when we say that in this course we teach you the most cutting-edge Deep Learning models and techniques.
- MoreTools- Theano is another That's what we mean when we say that in this course we teach you the most cutting-edge Deep Learning models and techniques.
- MoreTools- Theano is another That's what we mean when we say that in this course we teach you the most cutting-edge Deep Learning models and techniques.
- MoreTools- Theano is another
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